Method and system for fusing disparate industrial asset event information

ABSTRACT

There is provided a method and system for monitoring an asset. For example, there is provided a method that includes executing, by a system configured to monitor the asset, a series of operations that can include fetching, from a database communicatively coupled to the system, a data structure including information relative to one or more sources containing event data relative to the asset. The method may include generating, from the data structure, a first table including a list of sources. The method may include generating, from the data structure, a second table including a list of unique consolidated events. The method may include generating, based on a set of predetermined rules, a mapping table configured to relate the first table and the second table. The method may include associating, based on the mapping table, an event in the second table to the one or more sources in the first table.

TECHNICAL FIELD

The present disclosure generally relates to industrial assets. Moreparticularly, the present disclosure relates to a method and a systemfor fusing disparate industrial asset event information.

BACKGROUND

High value assets such as aircraft, jet engines, wind turbines, trains,ships, etc. are often interfaced with one or more monitoring systemsthat populate databases with data relative to events occurring duringoperation and/or during maintenance. An event may be broadlycharacterized herein as an occurrence in the life cycle of an asset. Forexample, and without limitation, an occurrence may include maintenanceactions (e.g., cleaning, replacing components, etc.) or failure events(e.g., unexpected shut downs, component wear, etc.). Furthermore, anoccurrence may include on-board fault messages or monitoring alerts.

Depending on when and where the asset is being monitored, an event maybe duplicated across several databases and in different contexts andaccording diverging data formats. This unwanted redundancy increasesrisks and maintenance costs, as it can be cumbersome to retrieve andunderstand event data from a plethora of sources. For example, thisunwanted redundancy may cause delays in taking required action when anevent is a critical fault.

SUMMARY

The embodiments featured herein help solve or mitigate the above-notedissues as well as other issues known in the art. For example, some ofthe embodiments featured herein include a system and a method of usethereof that are configured to monitor, fuse and classify asset eventdata in order to generate actionable information. Each of these kinds ofevents may be stored in different databases/tables, which each mayrecord the same event but using a different language or in a differentformat. The embodiments provided herein provide software methods andhardware that are configured to group related events, track usefulinformation, categorize events based on a confidence of the source(s)used, and highlight conflicting information.

For example, in one embodiment, there is provided a method formonitoring an asset. The method includes executing, by a systemconfigured to monitor the asset, a series of operations that can includefetching, from a database communicatively coupled to the system, a datastructure including information relative to one or more sourcescontaining event data relative to the asset. The method may includegenerating, from the data structure, a first table including a list ofsources. The method may include generating, from the data structure, asecond table including a list of unique consolidated events. The methodmay include generating, based on a set of predetermined rules, a mappingtable configured to relate the first table and the second table. Themethod may include associating, based on the mapping table, an event inthe second table to the one or more sources in the first table.

In yet another embodiment, there is provided a method for monitoring anasset. The method may include executing, by a system configured tomonitor the asset, a series of operations that can include fetching,from a database communicatively coupled to the system, a data structureincluding information relative to one or more sources containing eventdata relative to the asset. The method may include generating, from thedata structure, a first table including a list of sources.

The method may further include generating, from the data structure, asecond table including a list of unique consolidated events. The methodmay include generating, based on a set of predetermined rules, a mappingtable configured to relate the first table and the second table. Themethod may include executing, based on the mapping table, the firsttable, and the second table, a control subroutine configured toassociate a set of events with a corresponding set of sources. Themethod may further include dynamically categorizing the set of eventsinto known and unknown events.

In yet another embodiment, there is provided a system for monitoring anasset. The system includes a processor and a memory includinginstructions that, when executed by the processor, cause the processorto perform certain operations that include fetching, from a databasecommunicatively coupled to the system, a data structure includinginformation relative to one or more sources containing event datarelative to the asset. The operations may further include generating,from the data structure, a first table including a list of sources.

The operations may include generating, from the data structure, a secondtable including a list of unique consolidated events. The operations mayinclude generating, based on a set of predetermined rules, a mappingtable configured to relate the first table and the second table. Theoperations may include executing, based on the mapping table, the firsttable, and the second table, a control subroutine configured toassociate a set of events with a corresponding set of sources. Theoperations may include dynamically categorizing the set of events intoknown and unknown events.

Additional features, modes of operations, advantages, and other aspectsof various embodiments are described below with reference to theaccompanying drawings. It is noted that the present disclosure is notlimited to the specific embodiments described herein. These embodimentsare presented for illustrative purposes only. Additional embodiments, ormodifications of the embodiments disclosed, will be readily apparent topersons skilled in the relevant art(s) based on the teachings provided.

BRIEF DESCRIPTION OF THE DRAWINGS

Illustrative embodiments may take form in various components andarrangements of components. Illustrative embodiments are shown in theaccompanying drawings, throughout which like reference numerals mayindicate corresponding or similar parts in the various drawings.

Furthermore, the drawings are only for purposes of illustrating theembodiments and are not to be construed as limiting the disclosure.Given the following enabling description of the drawings, the novelaspects of the present disclosure should become evident to a person ofordinary skill in the relevant art(s).

FIG. 1. illustrates a method according to an embodiment.

FIG. 2. illustrates another method according to an embodiment.

FIG. 3. illustrates a system according to an embodiment.

DETAILED DESCRIPTION

While the illustrative embodiments are described herein for particularapplications, it should be understood that the present disclosure is notlimited thereto. Those skilled in the art and with access to theteachings provided herein will recognize additional applications,modifications, and embodiments within the scope thereof and additionalfields in which the present disclosure would be of significant utility.

In one embodiment, there is provided a method 100 that may be executedon an application-specific system. The method 100 may include a step 101that includes creating a source definition table (i.e., a table 102) fortracking one or more sources from which event information related to anasset may originate. For example, and not by limitation, the table 102may include a database name, a schema name, or a table name where theevent data is located. In one implementation where a graphical userinterface is available, creating the table 102 may include creating aview, or it may include a SQL select statement.

The table 102 may include one or more fields that include date and timeinformation pertaining to the event and the source from which itoriginates. Furthermore, the table 102 may also include one or morefields to identify the asset. In a step 103, the method 100 may includecreating a table 104 listing all the unique consolidated event namesthat need to be tracked. In one exemplary implementation, the table 104may be hierarchical. For instance, for when the asset is a jet engine,the table 104 may include a hierarchical level for a module of the jetengine (e.g., for a fan, a compressor, a combustor, a turbine, anindication, etc.). The table 104 may then further include anotherhierarchical level that includes information relating to specific faultswithin that module (e.g. turbine blade faults and/or shroud or nozzledamage).

The method 100 may further have a step 105 that includes creating amapping table 106 configured to map each source (i.e., entries from thetable 102) to unique events in the table 104. In an exemplaryimplementation, the mapping table 106 may include creating SQLstatements for each relevant source and event combination. Further,optionally, each source from the table 102 may be assigned a weightcorresponding to a measure of reliability of the source relative toanother source or to a predetermined benchmark. Furthermore, optionally,the sources of the table 102 may also be ranked according the severityof events associated with the sources (e.g., an in-service disruption ismore severe than routine maintenance which is more severe than analert).

FIG. 2 illustrates a method 200 that is configured to fuse informationfrom a wide variety of sources to generate actionable informationrelative to an asset. The method 200 may begin at a step 202 by firstexecuting the method 100, which generates the tables 102, 104, and 106.Furthermore, the method 200 may include executing a control subroutine(e.g., a loop) at step 204, to fetch all the sources including datarelative to an asset defined in the table 102. Next, in a step 206, themethod 200 may include using the tables 106 along with the tables 102and 104 to construct a query that returns a list of event types presentin the source tables present in the table 102. When no condition is met(i.e., when no event is found based on the mapping between the tables104 and 102), the step 206 may include setting an event type to “NULL”.Alternately, if an event is found but not listed in the table 104, theevent may be marked as “UNKNOWN.”

The method 200 may further include a step 208 that includes creating alist of all events and appending all sources together in a predeterminedorder. For example, and not by limitation, the predetermined order maybe that of a list that is sorted chronologically. In an exemplaryimplementation, the list may be sorted according to an event date (e.g.,from first logged event to last logged event) and it may also feature anidentifier pertaining to the asset, the event dates, a source, the eventtypes and a description of the events.

The method 200 may further include a step 210 where a loop is conductedover the plurality of assets identified in the previous steps. In oneexemplary embodiment, the loop may be conducted twice; in a first pass,the loop may identify unknown event types that are not linked but thatare kept for later assessment. In a second pass, the loop may identifythe event types that are linked successfully, in which case the weightsindicating the severity of each event found may be used to compute anoverall severity measure.

For example, the new overall severity measure may be computed asfollows:new_overall_severity=old_overall_severity+new_source_severity*(1−old_overall_severity).The method 200 may then include a step 212 where a loop is conductedover the weights table rows that relate to a particular source, inreverse order of weight magnitude (e.g., with the highest weighted beingaccessed first).

The method 200 further includes creating an output field indicating theevent type from each source being combined. For example, a first eventname that is not ‘unknown’ may be used as an event name for this source.If the event name does not match from different event mappings, themethod 200 may include using the first one found (i.e., with the highestconfidence) then increment a conflict counter and subsequently reducethe confidence. As such, the exemplary method 200 includes provisionsfor dynamically providing a confidence measure.

If the group of events is read as “no fault found” (NFF), which is aspecial case, the method 200 does not use it to create a new event butmay use it to reduce the confidence. Furthermore, when the event name isnot classified as “UNKNOWN”, the method 200 may include searching formatching events that have the same event group and that are within apredetermined time limit (e.g., 30 days).

Furthermore, if the event name is “UNKNOWN” but the loop is on itssecond pass, then the method 200 includes matching any event withinanother predetermined time limit that is tighter than the previouspredetermined time lit. (e.g., 7 days). If any matches are found, thenthe method 200 further includes looping over them and updating themaccordingly.

Furthermore, if a source is not in the sources list then, the method 200adds it to the list of sources and increments the confidence. In oneexemplary embodiment, this may be achieved as follows:new_overall_confidence=old_overall_confidence+new_source_confidence*(1−old_overall_confidence).Furthermore, the method 200 can append a description text when the eventconflicts or event names don't match. Otherwise, i.e., when no matchesfound, the method 200 creates a new record. Moreover, the method 200 maybe configured to add information about the sources used, such as a querythat will bring back all the relevant data from the merged sources. Themethod 200 may then update a database with the new event list, fromwhich a technician may gather actionable information regarding eventsoriginating from disparate sources.

Having described several exemplary methods and processes, anapplication-specific system that is configured to undertake theseprocesses is now described. FIG. 3 depicts a system 300 that includes anapplication-specific processor 314 configured to perform tasks specificto event classification, fusion, and asset monitoring in general.

The processor 314 has a specific structure imparted by instructionsstored in a memory 302 and/or by instructions 318 that can be fetched bythe processor 314 from a storage medium 320. The storage medium 320 maybe co-located with the processor 314, or it may be located elsewhere andbe communicatively coupled to the processor 314 via a communicationinterface 316, for example. Furthermore, in some embodiments, the system300 may be part of a cloud-based computing infrastructure providingcloud-based computing services.

The system 300 can be a stand-alone programmable system, or it can be aprogrammable module located in a much larger system. For example, thesystem 300 be part of a distributed system configured to handle thevarious modules of the process 100 described above. The processor 314may include one or more hardware and/or software components configuredto fetch, decode, execute, store, analyze, distribute, evaluate, and/orcategorize information. Furthermore, the processor 314 can include aninput/output module (I/O module 312) that can be configured to ingestdata pertaining one or more source databases 108.

The processor 314 may include one or more processing devices or cores(not shown). In some embodiments, the processor 314 may be a pluralityof processors, each having either one or more cores. The processor 314can be configured to execute instructions fetched from the memory 302,i.e. from one of memory block 304, memory block 306, memory block 308,and memory block 310.

Furthermore, without loss of generality, the storage medium 320 and/orthe memory 302 may include a volatile or non-volatile, magnetic,semiconductor, tape, optical, removable, non-removable, read-only,random-access, or any type of non-transitory computer-readable computermedium. The storage medium 320 may be configured to log data processed,recorded, or collected during the operation of the processor 314.

The data may be time-stamped, location-stamped, cataloged, indexed, ororganized in a variety of ways consistent with data storage practice.The storage medium 320 and/or the memory 302 may include programs and/orother information that may be used by the processor 314 to perform tasksconsistent with those described herein. For example, the processor 314may be configured by instructions from the memory block 306, the memoryblock 308, and the memory block 310, to perform the methods 100 and 200described above. The processor 314 may execute the aforementionedinstructions from memory blocks, 306, 308, and 310, i.e., an assetmonitoring core 305 of the memory 304, to execute a set of operationsconsistent with the methods 100 and 200.

Those skilled in the relevant art(s) will appreciate that variousadaptations and modifications of the embodiments described above can beconfigured without departing from the scope and spirit of thedisclosure. Therefore, it is to be understood that, within the scope ofthe appended claims, the disclosure may be practiced other than asspecifically described herein.

1. A method for monitoring an asset, the method comprising: executing,by a system configured to monitor the asset, a series of operationscomprising: fetching, from a database communicatively coupled to thesystem, a data structure including information relative to one or moresources containing event data relative to the asset; generating, fromthe data structure, a first table including a list of sources comprisingthe one or more sources; generating, from the data structure, a secondtable including a list of unique consolidated events; generating, basedon a set of predetermined rules, a mapping table configured to relatethe first table and the second table; associating, based on the mappingtable, an event in the second table to the one or more sources definedin the list of sources of the first table.
 2. The method of claim 1,wherein the second table is hierarchical.
 3. The method of claim 1,wherein the first table includes a source name, a schema name, or atable name where event data are located.
 4. The method of claim 3,wherein an entry in the first table includes a SQL select statement. 5.The method of claim 1, wherein the first table includes date and timeinformation pertaining to a specified source of the list of sources. 6.The method of claim 1, wherein the mapping table includes SQLstatements.
 7. The method of claim 1, wherein the method furtherincludes assigning a weight to each source of the list of sources in thefirst table.
 8. The method of claim 7, wherein each of the weightscorresponds to a measure of severity of a specified event associated toa specified source of the list of sources.
 9. The method of claim 1,further comprising ranking sources of the list of sources in the firsttable according to measures of event severity.
 10. A method formonitoring an asset, the method comprising: executing, by a systemconfigured to monitor the asset, a series of operations comprising:fetching, from a database communicatively coupled to the system, a datastructure including information relative to one or more sourcescontaining event data relative to the asset; generating, from the datastructure, a first table including a list of sources comprising the oneor more sources; generating, from the data structure, a second tableincluding a list of unique consolidated events; generating, based on aset of predetermined rules, a mapping table configured to relate thefirst table and the second table; executing, based on the mapping table,the first table, and the second table, a control subroutine configuredto associate a set of events with a corresponding set of sources fromthe list of sources; and dynamically categorizing the set of events intoknown and unknown events.
 11. The method of claim 10, wherein controlsubroutine is a loop.
 12. The method of claim 10, further comprisingcreating a new event type during a second iteration of the controlsubroutine when a first iteration yields an unknown event.
 13. Themethod of claim 10, further comprising an overall severity measure forthe set of events.
 14. A system for monitoring an asset, the systemcomprising: a processor; a memory including instructions that, whenexecuted by the processor, cause the processor to perform operationsincluding: fetching, from a database communicatively coupled to thesystem, a data structure including information relative to one or moresources containing event data relative to the asset; generating, fromthe data structure, a first table including a list of sources comprisingthe one or more sources; generating, from the data structure, a secondtable including a list of unique consolidated events; generating, basedon a set of predetermined rules, a mapping table configured to relatethe first table and the second table; executing, based on the mappingtable, the first table, and the second table, a control subroutineconfigured to associate a set of events with a corresponding set ofsources from the list of sources; and dynamically categorizing the setof events into known and unknown events.
 15. The system of claim 14,wherein the control subroutine is a loop.
 16. The system of claim 14,wherein the operations further include creating a new event type duringa second iteration of the control subroutine when a first iterationyields an unknown event.
 17. The system of claim 14, wherein theoperations further include computing an overall severity measure for theset of events.
 18. The system of claim 14, wherein the operationsfurther include assigning a weight to each source of the list of sourcesin the first table.
 19. The system of claim 18, wherein each of theweights corresponds to a measure of severity of a specified eventassociated to a specified source of the list of sources.
 20. The systemof claim 14, wherein the operations further include ranking sources ofthe list of sources in the first table according to measures of eventseverity.